Analysis of bibliometric indicators for individual scholars in a large data set

Citation numbers and other quantities derived from bibliographic databases are becoming standard tools for the assessment of productivity and impact of research activities. Though widely used, still their statistical properties have not been well established so far. This is especially true in the case of bibliometric indicators aimed at the evaluation of individual scholars, because large-scale data sets are typically difficult to be retrieved. Here, we take advantage of a recently introduced large bibliographic data set, Google Scholar Citations, which collects the entire publication record of individual scholars. We analyze the scientific profile of more than 30,000 researchers, and study the relation between the h-index, the number of publications and the number of citations of individual scientists. While the number of publications of a scientist has a rather weak relation with his/her h-index, we find that the h-index of a scientist is strongly correlated with the number of citations that she/he has received so that the number of citations can be effectively be used as a proxy of the h-index. Allowing for the h-index to depend on both the number of citations and the number of publications, we find only a minor improvement.     

Improving the performance of fuzzy rules-based forecasters through application of FCM algorithm

Prediction models based on artificial intelligence techniques have been widely used in Time Series Forecasting in several areas. They are often fuzzy models or neural networks. This paper describes the development of neural and fuzzy models for forecasting time series of practical examples, and shows the comparisons of results between models, including the results of statistical modeling. The use of data clustering algorithms like Fuzzy C-Means is considered in fuzzy models.     

Too Low to Kill: Concentration of the Secondary Metabolite Ranunculin in Buttercup Pollen does not Affect Bee Larval Survival

Growing evidence suggests that the freely accessible pollen of some plants is chemically protected against pollen-feeding flower visitors. For example, a diet of pollen from buttercup plants (Ranunculus) recently was shown to have a deleterious effect on developing larvae of several bee species not specialized on Ranunculus. Numerous Ranunculus species contain ranunculin, the glucosyl hydrate form of the highly reactive and toxic lactone protoanemonin, that causes the toxicity of these plants. We tested whether the presence of ranunculin is responsible for the lethal effects of R. acris pollen on the larvae of two bee species that are not Ranunculus specialists. To investigate the effect on bee larval development, we added ranunculin to the pollen provisions of the Campanula specialist bee Chelostoma rapunculi and the Asteraceae specialist bee Heriades truncorum, and allowed the larvae to feed on these provisions. We quantified ranunculin in pollen of R. acris and in brood cell provisions collected by the Ranunculus specialist bee Chelostoma florisomne. We demonstrated that although ranunculin was lethal to both tested bee species in high concentrations, the concentration in the pollen of R. acris was at least fourfold lower than that tolerated by the larvae of C. rapunculi and H. truncorum in the feeding experiments. Ranunculin concentration in the brood cells of C. florisomne was on average even twentyfold lower than that in Ranunculus pollen, suggesting that a mechanism different from ranunculin intoxication accounts for the larval mortality reported for bees not specialized on Ranunculus pollen.     

Living Lab: A Methodology between User‐Centred Design and Participatory Design

Living Labs have received limited attention in the literature despite their diffusion throughout Europe and recent interest from policy makers. This limited attention is linked to the newness of the phenomenon, the high heterogeneity of cases and the consequent lack of definitions and acknowledged frameworks for scholarly analyses. In this work, we argue that the originality of the Living Lab phenomenon resides in the introduction of a new methodology. Using an analysis of the literature and case studies, we propose a new definition, position this methodology among other design methodologies and highlight its peculiarities. We underline the co‐creative potentialities, the awareness of users and the real‐life settings. Furthermore, our case‐based research allows us to identify four different specifications for this methodology, and therefore four different types of Living Labs, based on the openness of the user involvement and the adopted platform technology.     

Perfluoropolyether polymers by UV curing: design,synthesis and characterization

Perfluoropolyether (PFPE) structures can be functionalized with acrylic groups using appropriate hydrogenated acrylic monomers: the macromers obtained are highly reactive under UV irradiation, and fluorinated polymers can be obtained. In the first part of this work is described the synthesis of new PFPE (meth)acrylic oligomers by extending OH‐terminated fluorinated chains with urethane groups and reactive acrylic functions. The photopolymerization reaction of each product is then reported followed by the characterisation of the main thermal, mechanical and surface properties of UV‐cured coatings. The polymers have good thermal resistance and fair mechanical and chemical resistance. More interestingly they show very low refractive index and low surface tension. For these latter properties the products can be advantageously used in highly demanding applications such as photonic devices and nano‐patterning. Copyright © 2011 Society of Chemical Industry     

Caffeic Acid Enhances the Anti-Leukemic Effect of Imatinib on Chronic Myeloid Leukemia Cells and Triggers Apoptosis in Cells Sensitive and Resistant to Imatinib

Among the phenolic acids tested on the K562 cell line, a model of chronic myeloid leukemia (CML), caffeic acid (CA) was biologically active on sensitive and imatinib (IM)-resistant cells at micro-molar concentration, either in terms of reduction of cell proliferation or triggering of apoptosis. The CA treatment provoked mitochondrial membrane depolarization, genomic DNA fragmentation and phosphatidylserine exposure, hallmarks of apoptosis. Cell cycle analysis following the treatment with comparable cytotoxic concentrations of IM or CA showed marked differences in the distribution profiles. The reduction of cell proliferation by CA administration was associated with increased expression of two cell cycle repressor genes, CDKN1A and CHES1, while IM at a cytotoxic concentration increased the CHES1 but not the CDKN1A expression. In addition, CA treatment affected the proliferation and triggered the apoptosis in IM-resistant cells. Taken together, these data suggested that CA induced the anti-proliferative effect and triggered apoptosis of CML cells by a different mechanism than IM. Finally, the combined administration of IM and CA at suboptimal concentrations evidenced a synergy of action in determining the anti-proliferative effect and triggering apoptosis. The ability of CA to potentiate the anti-leukemic effect of IM highlighted the nutraceutical potential of CA in CML.     

A semantic role labelling-based framework for learning ontologies from Spanish documents

Currently, most of the information available in the Web is adapted primarily for human consumption, but there is so much information that can no longer be processed by a person in a reasonable time, either in digital or physical formats. To solve this problem, the idea of the Semantic Web arose. The Semantic Web deals with adding machine-readable information to Web pages. Ontologies represent a very important element of this web, as they provide a valid and robust structure to represent knowledge based on concepts, relations, axioms, etc. The need for overcoming the bottleneck provoked by the manual construction of ontologies has generated several studies and research on obtaining semiautomatic methods to learn ontologies. In this sense, this paper proposes a new ontology learning methodology based on semantic role labeling from digital Spanish documents. The method makes it possible to represent multiple semantic relations specially taxonomic and partonomic ones in the standardized OWL 2.0. A set of experiments has been performed with the approach implemented in educational domain that show promising results.     

Numerical simulation and experimental validation of a multi-step deep drawing process

This paper presents the numerical simulation of an industrial multi-step deep drawing process. A large strain finite element formulation including a hyperelastic elastoplastic constitutive model and a contact-friction law is used to this end where the steel sheet material parameters considered in the analysis are previously derived through a characterization procedure of its mechanical response. The numerical predictions of the final shape and thickness distribution of the blank are compared and discussed with available experimental values measured at the end of three successive drawing steps. In addition, a plastic work-based damage index is used to assess failure occurrence during the process. The damage values computed at the end of the drawing process are found to be lower than that corresponding to rupture in the tensile test, considered here as the threshold of failure, confirming, as observed experimentally, that neither fracture nor necking is developed in the blank during the whole drawing process. Finally, the possibility to carry out a reduced two-step drawing process, obtained by merging the second and third steps of the three-step process, is precluded since the damage criterion predicts in this case excessively large values that indicate that failure may occur in specific zones of the sheet.